A Scalable Approach for QoS-Based Web Service Selection

  • Mohammad Alrifai
  • Thomas Risse
  • Peter Dolog
  • Wolfgang Nejdl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5472)


QoS-based service selection aims at finding the best component services that satisfy the end-to-end quality requirements. The problem can be modeled as a multi-dimension multi-choice 0-1 knapsack problem, which is known as NP-hard. Recently published solutions propose using linear programming techniques to solve the problem. However, the poor scalability of linear program solving methods restricts their applicability to small-size problems and renders them inappropriate for dynamic applications with run-time requirements. In this paper, we address this problem and propose a scalable QoS computation approach based on a heuristic algorithm, which decomposes the optimization problem into small sub-problems that can be solved more efficiently than the original problem. Experimental evaluations show that near-to-optimal solutions can be found using our algorithm much faster than using linear programming methods.


  1. 1.
    OASIS: Web services business process execution language (April 2007),
  2. 2.
    Pisinger, D.: Algorithms for Knapsack Problems. PhD thesis, University of Copenhagen, Dept. of Computer Science (1995)Google Scholar
  3. 3.
    Nemhauser, G.L., Wolsey, L.A.: Integer and Combinatorial Optimization. Wiley-Interscience, New York (1988)CrossRefzbMATHGoogle Scholar
  4. 4.
    Zeng, L., Benatallah, B., Dumas, M., Kalagnanam, J., Sheng, Q.Z.: Quality driven web services composition. In: WWW, pp. 411–421 (2003)Google Scholar
  5. 5.
    Ardagna, D., Pernici, B.: Adaptive service composition in flexible processes. IEEE Trans. Software Eng. 33(6), 369–384 (2007)CrossRefGoogle Scholar
  6. 6.
    Liu, Y., Ngu, A.H.H., Zeng, L.: Qos computation and policing in dynamic web service selection. In: WWW, pp. 66–73 (2004)Google Scholar
  7. 7.
    Yu, T., Zhang, Y., Lin, K.J.: Efficient algorithms for web services selection with end-to-end qos constraints. ACM Trans. Web 1(1), 6 (2007)CrossRefGoogle Scholar
  8. 8.
    Maros, I.: Computational Techniques of the Simplex Method. Springer, Heidelberg (2003)CrossRefzbMATHGoogle Scholar
  9. 9.
    Li, F., Yang, F., Shuang, K., Su, S.: Q-peer: A decentralized QOS registry architecture for web services. In: Krämer, B.J., Lin, K.-J., Narasimhan, P. (eds.) ICSOC 2007. LNCS, vol. 4749, pp. 145–156. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  10. 10.
    Yoon, K.P., Hwang, C.L.: Multiple Attribute Decision Making: An Introduction (Quantitative Applications in the Social Sciences). Sage Publications, Thousand Oaks (1995)CrossRefGoogle Scholar
  11. 11.
    Berkelaar, M., Kjell Eikland, P.N.: Open source (mixed-integer) linear programming system. Sourceforge,
  12. 12.
    Al-Masri, E., Mahmoud, Q.H.: Investigating web services on the world wide web. In: WWW (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Mohammad Alrifai
    • 1
  • Thomas Risse
    • 1
  • Peter Dolog
    • 2
  • Wolfgang Nejdl
    • 1
  1. 1.L3S Research CenterLeibniz University of HannoverGermany
  2. 2.Department of Computer ScienceAalborg UniversityDenmark

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